Canberra 2019 | Software
Systematic Maps are, according to the Environmental Evidence Journal, “overviews of the quantity and quality of evidence in relation to a broad (open) question of policy or management relevance.” In simple terms, this means that documents are categorized according to the type, location, and publication information available for each work within a particular topic. Systematic maps are often used for environmental research, where it is particularly important to track the location of study sites. The spatial nature of a systematic map, particularly for environmental research, means that academics often use some kind of geographic map to analyze and present their information. Understanding the academic community’s familiarity with the R programming language, we built a webapp using R Shiny that could automate certain parts of creating a systematic map for environmental research.
Forestr is an online platform for interactive visualisations of forest plots.
In evidence synthesis it is relatively easy to find published literature on a given topic, and to record what the search string was used in which database, how many records were found, how many were used or not used and why. It is much more difficult to be systematic in searching and recording grey literature.
The metadat package contains a large collection of meta-analysis datasets. These datasets are useful for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.
Evidence synthesis (ES) is the process of identifying, collating and synthesising primary scientific research (such as articles and reports) for the purposes of providing reliable, transparent summaries. The goal of this project is to collect, integrate and expand the universe of available functions for ES projects in R, via our proposed metaverse package. Like tidyverse, metaverse is envisioned as a collector package that makes it straightforward to install a set of functions - currently located in separate packages - for a common purpose.
Automation tools are speeding up the conduct of evidence synthesis. However, the uptake of these tools amongst reviewers are slow. Potential barriers to use are; 1) the tools often operate in isolation, 2) reviewers need to manipulate their citation data into a specific format to use the tool, and 3) different tools require different levels of programming or computing expertise.
robvis is an R package that allows users to quickly visualise risk-of-bias assessments performed as part of a systematic review. It allows users to created weighted bar-plots of the distribution of risk-of-bias judgements within each bias domain, in addition to “traffic light” plots of the specific domain-level judgements for each study. The resulting figures are formatted according the risk-of-bias assessment tool use to perform the assessments (currently supported tools are ROB-2, ROBINS-I and QUADAS-2). An associated Shiny app provides a user-friendly interface for the tool.